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TheEvolutionofU.S.CommunityBanksandItsImpactonSmallBusinessLending
JulapaJagtiani*
IanKotliar@
RamanQuinnMaingi@
October23,2014
AbstractThere have been increasing concerns about the potential of larger banks acquiring community
banks and the declining number of community banks, which would significantly reduce small business lending (SBL) and disrupt relationship lending. This paper examines the roles and characteristics of U.S. community banks in the past decade, covering the recent economic boom and downturn. We analyze risk characteristics (including the confidential ratings assigned by bank regulators) of acquired community banks, compare pre‐ and post‐acquisition performance and stock market reactions to these acquisitions, and investigate how the acquisitions have affected SBL. Contrary to concerns, we find that the overall amount of SBL tends to increase after a large bank acquires a community bank. The ratio of SBL to assets does decline in the large acquiring banks but at a slower rate than the decline seen in surviving community banks. Further, community banks that were merged during the financial crisis were mostly in poor financial condition, had been rated as unsatisfactory by their regulators on all risk aspects, and would have been unlikely to continue lending. We found that community bank targets accepted smaller merger premiums (or even discounts) to be part of a large banking organization. Our results indicate that mergers involving community bank targets over the past decade have enhanced the overall safety and soundness of the banking system without adversely impacting SBL. This implies that a policy that discourages mergers between community banks and large banks is unwarranted and could potentially result in a weaker financial system and have an unintentional dampening effect on the supply of SBL.
JEL Classifications: G21, G28, G34 Keywords: Community Bank, Small Business Lending, Bank Mergers ______________________ *Please direct correspondence to Julapa Jagtiani, Federal Reserve Bank of Philadelphia, Supervision, Regulation & Credit Department, Ten Independence Mall, Philadelphia, PA 19106; 215‐574‐7284; e‐mail: [email protected]. The authors thank Allen Berger, Mitch Berlin, Paul Calem, and Bill Lang for their valuable comments and suggestions. Thanks also to Vince Poppa for his data support and Juanzi Li for her dedicated research assistance. @Both Kotliar and Maingi were students at Rutgers when this paper was written. The views in this paper are the authors’ and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. This paper is available free of charge at www.philadelphiafed.org/research‐and‐data/publications/working‐papers/.
2
I. IntroductionThe recent financial crisis has resulted in a dramatic increase in the number of problem
banks — from 50 problem banks in 2005 to a peak of 884 in 2010. As of March 2013, there
were still 612 problem banks.1 Most of these have been small community banks with an
average asset size of about $450 million. The stock market recovered and reached its new high
in 2013, and large banks, particularly the too‐big‐to‐fail (TBTF) or systemically important
financial institutions, have also recovered strongly.2 However, affected community banks have
remained troubled.
While the Dodd‐Frank Wall Street Reform and Consumer Protection Act has focused
mostly on large TBTF banks, there have been fears among small community banks that they
might also be affected and that the new rules might inhibit their ability to lend in their local
communities because of the increased costs of such lending.3 For these reasons, some
commentators believe that many of the community banks have been seeking to merge or to be
acquired by a larger bank in order to take advantage of the scale economies under the new
regulations.4 Should community banks be encouraged to merge? Would acquisitions of
community banks by large banks result in a significant reduction in SBL in local communities
and destroy relationship lending?
1 Source: FDIC Report 2 For example, JPMorgan Chase & Co. reported profit growth of 31 percent per share in the second quarter of 2013, Goldman Sachs’s profit also more than doubled in the second quarter of 2013 compared with the year before, and Bank of America reported a 65 percent increase in profit during the same period. 3 This concern holds despite the recent efforts to impose less complex requirements for small banks, such as the Volcker Rule, which was approved by the Senate in December 2013. 4 In December 2013, the Conference of State Bank Supervisors released a paper on designing a federal regulatory framework for community banks. The group has argued that the rulemaking since the financial crisis has undermined the smaller lenders’ ability to provide credit tailored to consumers and small businesses. See Conference of State Bank Supervisors (2013) for more details.
3
Our objective is to examine the impact of small community bank acquisitions by large
banks on SBL over the past decade, covering both the boom and the recent downturns. The
measures of performance and risk characteristics used in this study include the change in the
confidential supervisory ratings (CAMELS) before and after the mergers; how the banks perform
in terms of risk‐taking, efficiency, liquidity, capitalization, and profitability; and how they are
perceived by the market. We use the data on mergers and acquisitions that involved
community banks during the period from 2000 to 2012 to examine the risk characteristics of
the targets and acquirers at the time of the mergers, to track postmerger performance of the
combined banking firm, and to investigate whether the mergers have affected the banks’ SBL.
Finally, we observe how the stock markets react to the community bank merger
announcement, during both the boom and the financial crisis.
We find that community bank mergers that took place during the recent financial crisis
are much different than those mergers that occurred in earlier periods (examined in previous
studies). We find that mergers of community banks with other (healthier) banks have resulted
in combined banking firms that are healthier financially and more efficient in their operations.
Controlling for the risk characteristics of the targets and their acquirers and for economic
factors, we find that overall SBL tends to increase when the acquirer is a large bank (with assets
of more than $10 billion). Overall, mergers that involved community bank targets have so far
enhanced the safety and soundness of the banking system and have done so without hurting
SBL, as large banks have come in to substitute and fill the SBL gap.
The rest of the paper is organized as follows. Section II discusses existing literature
related to the special role of community banks in relationship lending and those related to the
4
impact of community bank mergers on credit availability to small businesses. Section III
describes the data sources and provides a statistical overview of the changes in the U.S.
community banking industry since the year 2000. Section IV explores the risk characteristics of
the targets, the acquiring banks, and the combined banking firms for all the mergers that
involved community bank targets since the year 2000 — and shows that community banks have
become stronger through the mergers and acquisitions. Section V investigates the evolving role
of community banks in SBL over the 2000–2012 period by exploring SBL market shares at large
versus community banks, and how SBL may have been affected by community bank mergers.
Section VI examines merger deal premiums and stock market reactions in all mergers that
involved community bank targets during 2000–2012. Finally, concluding remarks and policy
implications are presented in Section VII.
II. LiteratureReviewandOurContribution
About 93 percent of all U.S. banks are community banks with total assets of less than $1
billion. These banks altogether, however, account for only about 10 percent of U.S. banking
assets (see Table 1 for more details). This may be why research that focuses on community
banks has been relatively scarce despite concerns about the impact of the recent recession on
this sector and the related policy considerations. We will focus on studies on community bank
mergers and the role of community banks in SBL.
Role of Community Banks in SBL: The existing literature on the role of community banks
in SBL has so far presented mixed results. Using merger data from 1991 to 2006, Beccalli and
Frantz (2013) examine important determinants for banks to become involved as either a target
or an acquirer in a merger. While the paper focuses primarily on methodological approaches —
5
multinomial logistic versus Cox regression — they find that banks that are likely to become a
target of a bank merger tend to be cost and profit inefficient, less liquid, and less capitalized.
They also find that the acquiring banks tend to be well diversified and well managed, where
managers leverage their profits and pursue higher growth strategies. Banks that acquire other
banks multiple times (involved in multiple merger deals rather a single deal) tend to be larger
banks. The results from Beccalli and Frantz (2013) imply that the acquirers of community banks
are likely to be larger banks, thus causing concerns that the combined banking firm would be
too large to look beyond credit scores and other model‐based metrics in its lending decision
and too large to maintain the direct personal knowledge of the local economy that has enabled
community banks to tailor products and services to meet community needs.
Kowalik (2013) examines how competition from large banks, which have lower funding
costs, affects small banks’ ability to attract and maintain their borrowers. Small community
banks have advantages in monitoring their customers through personal relationships, and they
have an important role to play in monitoring and enhancing the project value for intermediate
quality borrowers whose true quality may not be reflected in the public reports. The paper
argues that small banks can be viable competitors of large banks and can add value to the
borrowers’ projects when the true value cannot be easily observed by large banks. This finding
is consistent with the conventional paradigm, which suggests that, unlike large banks that serve
large transparent firms, small community banks have their special role in supporting small
businesses in their local communities, as they are better able to form strong relationships with
small opaque firms.
6
Other papers, however, seem to suggest the opposite findings. For example, Berger and
Udell (2006) examine lending to small and medium‐size enterprises (SME) using a more
complete framework that allows the presence of alternative lending technologies. They
conclude against some previous findings — that large banks have a comparative advantage in
transaction‐based lending technologies and that a comparative disadvantage in relationship
lending does not necessarily imply that large banks are disadvantaged in providing credit to
informationally opaque SMEs. They also add that some transaction‐based lending technologies
used by large banks are actually well suited for funding opaque SMEs. Further, previous
findings may be driven by the differences between the U.S. structure and that of other nations.
Small bank presence may be more important in other nations because their financial structures
may limit their use of some lending technologies available in the U.S.5
In addition, using the 2003 Survey of Small Business Finances, Berger, Goulding, and
Rice (2014) examine the type of bank serving as the main relationship bank for small
businesses, controlling for risk characteristics of the firm and those of the owner. They also find
results that are not consistent with the conventional paradigm.
Interestingly, Berger, Frame, and Miller (2005) find that small business credit score
(SBCS) plays an important role in SBL, as it reduces lending costs and allows for a net increase in
lending to “marginal borrowers.” Further, the SBCS has allowed some large banks to expand
their lending to at least some pools of small business customers — therefore, this technology
has allowed larger banks to increase their role in lending to small businesses.
5 The most recent review of bank lending technologies may be found in Berger (2014).
7
Berger, Cerqueiro, and Penas (2014) examine the contribution of small banks in lending
to recent startup firms during the period from 2004 to 2009. They find that the greater market
presence of small banks results in more lending to small opaque firms and a lower failure rate
of these small firms during normal times, but this only holds for information‐intensive loans,
such as term loans and business lines of credit. In addition, this relationship disappeared and
was reversed during the financial crisis. Consistent with these findings, Berger, Cowan, and
Frame (2011) find that the use of credit scores (rather than relationships) in SBL by community
banks is surprisingly widespread. Interestingly, the credit scores employed by community
banks tend to be the consumer credit scores of the small business owners rather than the more
encompassing SBCS that more accurately reflect credit information on both the firms and the
owners.
Community Bank Mergers and SBL Impacts: Jagtiani (2008) examines 3,900 mergers
that involved publicly traded banking organizations during the pre‐financial crisis period from
1990 to 2006. The results indicate that more than one‐half of the acquiring banks that bought
community banks were themselves community banks. This, in conjunction with another finding
that almost 90 percent of all mergers between community banks (during the period before the
financial crisis) involved banks headquartered in the same state, seems to suggest that
community banks may be merging with the goal of concentrating their efforts on what they are
believed to do best (which is to provide personal service to small businesses and other local
customers).
Elyasiani and Goldberg (2004) present a literature survey on SBL and suggest that while
bank mergers are likely to affect SBL, the decision for banking firms to make relationship loans
8
could also be affected by several other factors, such as regulatory and/or technological
changes, loan characteristics (such as collateral and loan rates), and borrower characteristics
(such as multiple relationships, length of relationship, distance, etc.).
Using data from older 1994 to 2000 and focusing on the role of community banks in SBL
lending, Avery and Samolyk (2004) examine how bank mergers affected SBL in local markets.
They find that while large bank mergers are associated with slower loan growth in the local
area, community bank mergers are associated with higher loan growth and greater market
share of SBL funded by community banks. This is consistent with Jagtiani (2008) and sheds light
on the source of increased SBL by community banks in the local area, since Jagtiani (2008) does
not examine reactions by other community banks in the local area in response to a community
bank merger. Avery and Samolyk (2004) take into account these reactions and conclude that
other community banks in the area react to mergers by making more SBL.
Berger, Scalise, Saunders, and Udell (1998) also found that other banks in the area had
strong SBL reactions to bank mergers, as the size distribution of banks in the local market
change. They investigate the “static” versus the “dynamic” effects of bank mergers on SBL.
They find that while the static effects (associated with scale and strategy due to reduced
efficiency in relationship lending as the banks merge into a larger bank) resulted in a reduction
in SBL, the dynamic effects (associated with postmerger impact and reactions by other local
banks) resulted in increased SBL by other banking firms in the local area. Overall, they conclude
that the static effects that reduce SBL are more than offset by the reactions of other local banks
so that the net impact of bank mergers results in increased SBL.
9
In addition to increased SBL from other nonmerged banks in the same local area,
Berger, Bonime, Goldberg, and White (2004) found that de novo banks spring up and start
engaging in SBL in markets in which there are mergers. Goldberg and White (1998) and
DeYoung, Goldberg, and White (1999) find that new banks tend to make more relationship
loans and that the amount of relationship lending declines as banks age (up to 20 years old). In
response to community bank mergers, de novo banks tend to be formed to fill the SBL gap as
small local banks disappear through mergers.
Overall, the literature suggests that there are many factors that impact the amount and
growth in SBL. Bank consolidation and reaction by other banks to local bank mergers could
impact SBL. Besides mergers and acquisitions, changes in market environment and regulations
could play an important role. The recent financial crisis has brought about one of the largest
changes in the history of banking regulations, resulting in dramatic changes in the behaviors of
both borrowers and banking firms. Our paper reexamines community bank mergers and SBL,
using more recent data.
III. CommunityBankingOverview
Our data come from various sources. All the information related to the mergers, target
characteristics, and the acquirer characteristics come from the SNL Financial database. Data
related to SBL are collected from the Federal Reserve Call Reports and Y‐9 Reports. Supervisory
ratings are collected from the National Examination Data (NED) System. Stock prices are from
the Center for Research in Security Prices (CRSP) database, and economic factors are collected
from the Haver Analytics database.
10
The U.S. banking industry is unique in that while more than 90 percent of about 7,000
U.S. banks are small community banks (with less than $1 billion in assets), more than 90
percent of the U.S. banking assets are held at large banking institutions.6 The community
banking sector has also been shrinking over time, both in terms of the number of community
banks and the amount of assets controlled by community banks (Table 1).
There has also been a long‐term, steady trend of merger and acquisition activity
involving community banks. Overall, the number of large banks has been growing significantly
in the past decade, while there has been a substantial decline in the number of community
banks. More than 90 percent of all bank merger transactions that took place during 2000 to
2012 involved community bank targets. However, this number translates to only about 10
percent in terms of all targets’ banking assets (Table 2).
There have been concerns that attrition of the community banking sector may be
adversely affecting SBL and that acquisition of small banks by large banking institutions would
disrupt relationship lending. The general perception seems to be that the observed decline in
the number of community banks in the past decade may not result in much impact on SBL if the
acquirers have been community banks themselves (rather than large banks). Table 3 shows
that community banks have been acquired mostly by other community banks throughout the
study period, especially during the period after the recent financial crisis began. In addition to
the acquirers’ asset size, there also have been concerns that if the acquiring banks are
headquartered in another state, the funding from the local community may be lost to out‐of‐
state borrowers. Table 4 shows that this has not been the case. Community bank mergers
6 This is as of year‐end 2012.
11
(mergers between the community bank target and the community bank acquirer) have mostly
been within the same state (in‐state mergers).
Overall, since most of the community bank mergers involved community bank acquirers
and were mostly in‐state mergers, the mergers should not have reduced lending to small
businesses and/or moved funds out of the community. In fact, community bank mergers that
took place in the past decade should have strengthened the banks’ comparative advantage in
relationship lending. The next sections further examine how community bank mergers have
affected their risk characteristics and their roles as relationship lenders to small businesses.
IV. HaveCommunityBanksBecomeStrongerorWeakerAftertheMergers?
We explore important characteristics of targets and acquirers around the mergers’
announcement dates and compare those with characteristics of the combined firm after the
mergers. Figures 1.1 to 1.7 present the comparison of premerger and postmerger performance
based on the various components of the confidential supervisory ratings (i.e., the capital
adequacy (C), asset quality (A), management quality (M), earnings (E), liquidity (L), sensitivity to
market (S), and the composite rating (CAMELS), respectively).7 The sample includes all mergers
that involved community banks during the period from 2000 to 2012. The plots compare
average ratings across all the mergers that were announced in each year from that period.
Note that the lowest rating (1) represents the best rating, and the highest rating (5) is the
worst.8
7 The premerger ratings for targets and acquirers are the latest assigned ratings prior to the merger announcement date. The postmerger ratings are the first assigned rating after the merger has been completed. 8 Agarwal, Lucca, Seru, and Trebbi (2014) find that different regulators may be applying different standards when assigning the CAMELS ratings. The discrepancy is related to different weights given to local economic conditions.
12
Based on the average supervisory ratings prior to the mergers, the community bank
targets are clearly weaker than the acquirers, particularly for mergers that took place during
the financial crisis period or later (2008 and thereafter) when the targets’ ratings were below
satisfactory (3 rating), on average. The ratings of the combined firm (after the merger) are
much improved compared with those of the targets prior to the mergers. These results are
consistent across all component ratings and the composite CAMELS rating.
Overall, community banks that were acquired during the financial crisis had performed
poorly and, on average, were rated unsatisfactory by their regulators on all risk aspects.9 These
banks would not have been able to serve as a good funding source for small businesses anyway,
and, in fact, they were more likely to fail if they were not acquired by another (healthier) bank.
Overall, these mergers actually served to enhance the safety and soundness of the banking
system,10 suggesting that there are no good reasons to be overly concerned about the large
number of community bank mergers so far.
While our analysis here does not control for the regulators (federal versus state regulators) that assigned the ratings, we do control for economic conditions around the merger date. 9 These community bank targets were undercapitalized, holding poor‐quality assets on the balance sheet, not well managed, not profitable, less liquid, and more exposed to greater market risks. 10 Our finding is consistent with Cooper and Vermilyea (2012), who find that mergers that involved a well‐managed acquiring bank (with a superior M rating) could improve the long‐term performance of the combined banking firm after the merger.
13
1
1.5
2
2.5
3
3.5
4
4.5
Figure 1.1: Capital Adequacy (C) Rating Targets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
1
1.5
2
2.5
3
3.5
4
4.5
Figure 1.2: Asset Quality (A) RatingTargets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
1
1.5
2
2.5
3
3.5
4
4.5
Figure 1.3: Management Quality (M) RatingTargets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
1
1.5
2
2.5
3
3.5
4
4.5
5
Figure 1.4: Earnings (E) RatingTargets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
1
1.5
2
2.5
3
3.5
4
Figure 1.5: Liquidity (L) RatingTargets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
1
1.5
2
2.5
3
3.5
4
Figure 1.6: The Market Sensitivity (S)Targets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
14
Sources: SNL database and the Federal Reserve
In addition to exploring changes in the confidential supervisory ratings, we confirm our
findings with additional analysis of other important performance measures for targets and
acquirers. Figures 2.1 to 2.5 present the various performance measures, based on the return
on equity (ROE), operational inefficiency ratio (measured as the ratio of noninterest expense to
the sum of net interest income and other income), nonperforming assets (NPA) ratio, loan–loss
reserve ratio, and common equity capital‐to‐total asset ratio, respectively. The results are
consistent with those presented earlier. Again, community bank targets are generally weaker
than the acquirers prior to the mergers, particularly for community bank mergers that took
place during and after the recent financial crisis.11
V. FundingAvailabilityforSmallBusinesses
The conventional wisdom is that small local community banks make loans based on
relationships and other qualitative information (rather than the typical model‐based risk score
11 The targets were not profitable (smaller ROE or larger losses), were less efficient in their operations, had more bad loans (more charge‐offs), and were less capitalized.
1
1.5
2
2.5
3
3.5
4
4.5
Figure 1.7: The Composite CAMELS RatingTargets vs. Acquirers vs. Postmergers
For Mergers in 2000‐2012
After
Target
Buyer
15
Source:SNLFinancialdatabase
‐15
‐10
‐5
0
5
10
15
20
2000 2002 2004 2006 2008 2010 2012
Figure 2.1: ROE For Targets vs. Acquirers Mergers Between Community Banks
Acquirers
Targets
55
60
65
70
75
80
85
90
95
100
Figure 2.2: Inefficiency Ratio for Targets vs. Acquirers
Mergers Between Community Banks
Acquirers
Targets
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Figure 2.3: NPA Ratio for Targets vs. AcquirersMergers Between Community Banks
Acquirers
Targets
0
50
100
150
200
250
300
350
400
Figure 2.4: Loan‐Loss Reserve Ratio ‐ Targets vs. Acquirers; Mergers Between Community Banks
Acquirers
Targets
8
9
10
11
12
13
14
Figure 2.5: Capital Asset Ratio for Targets. vs. Acquirers; Mergers Between Community Banks
Acquirers
Targets
16
used by large banks). The public concerns around community bank mergers and the declining
number of U.S. community banks have been mainly associated with the belief that community
banks have been the traditional funding sources for local small businesses and that there would
be a shortage of funds to small and new businesses without them. We explore the role of
community banks versus large banks in SBL and examine the potential impact of attrition of the
community banking sector on SBL.
SBL at Community Banks Versus Large Banks: First, we examine the changes in market
share of SBL for the various bank size groups from 2001 to 2012, using Call Report data.12
Figure 3.1 shows that SBL market share increased significantly (more than doubled) for the
largest banks (larger than $100 billion) but decreased for community banks.13 Second, we
examine the average SBL‐to‐total‐asset ratio for the various bank size groups during the same
period from 2001 to 2012.14 Figure 3.2 shows that the SBL‐to‐assets ratio has declined during
this period — for all bank size groups (including community banks). While community banks
have consistently been more committed (larger ratio of SBL to total assets) to SBL, this does not
translate to a large volume of SBL. More important, it is indicated in Figure 3.2 that since 2008
the average SBL‐to‐assets ratio has declined more sharply for the surviving community banks
than the larger banks.
12 Data on SBL and assets are obtained from the year‐end quarterly Call Reports, and the sample includes all banks (the entire market) in the U.S. 13 The increased market share in SBL at large banks is partly due to their becoming more active in SBL and partly due to the fact that large banks became larger in this period. The number of banks in this size category increased from six banks in 2001 to 18 banks in 2012, and their share of domestic assets increased from 36 percent in 2001 to 66 percent in 2012. 14 Again, data on SBL and assets are obtained from the year‐end quarterly Call Reports, and the sample includes all banks in the U.S.
17
Sources: SNL database and Call Reports
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%1‐Jan
‐01
1‐Jan
‐02
1‐Jan
‐03
1‐Jan
‐04
1‐Jan
‐05
1‐Jan
‐06
1‐Jan
‐07
1‐Jan
‐08
1‐Jan
‐09
1‐Jan
‐10
1‐Jan
‐11
1‐Jan
‐12
Figure 3.1: Fraction of Total $ SBL by Bank Size Group (2001‐2012) ̶̶̶̶ All Banks
Total Assets >$100B
$10B<TotalAssets<$100B
$1B<TotalAssets<$10B
CommunityBanks
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
1‐Jan
‐01
1‐Jan
‐02
1‐Jan
‐03
1‐Jan
‐04
1‐Jan
‐05
1‐Jan
‐06
1‐Jan
‐07
1‐Jan
‐08
1‐Jan
‐09
1‐Jan
‐10
1‐Jan
‐11
1‐Jan
‐12
Figure 3.2: SBL‐to‐Total Asset Ra o ̶̶̶̶ byBank Size Group (2001‐2012) ̶̶̶̶ All Banks
CommunityBanks
$1B<TotalAssets<$10B
$10B<TotalAssets<$100B
Total Assets >$100B
0
5
10
15
20
25
Small B
usiness Lending ($10,000,000s)
Figure 3.3: $ Amount of SBL as of Merger DateTargets vs. Acquirers
Target
Buyer
0.03
0.035
0.04
0.045
0.05
0.055
0.06
0.065
Figure 3.4: Ratio of SBL to Total Assets as of Merger Announcement Date: Targets vs. Acquirers
Target
Buyer
0.05
0.055
0.06
0.065
0.07
0.075
0.08
0.085
0.09
Figure 3.5: Ratio of SBL (with Farm) to Total Assets as of Merger Date: Targets vs. Acquirers
Target
Buyer
18
SBL at Community Banks That Merged: We then focus on SBL volume associated with
community banks that merged during the period from 2000 to 2012. In terms of SBL volume (in
dollar amount), Figure 3.3 shows that the targets had significantly smaller SBL, on average, than
the acquirers did.15 In terms of commitment to SBL (ratio of SBL to assets), however, Figures
3.4 and 3.5 show that the targets were more committed than the acquirers prior to the
mergers.16 We also find that after the mergers, SBL for the combined firms (as of one year and
two years after the completion of the mergers) tends to follow the acquirers’ patterns.
The overall results so far suggest that while the U.S. banking industry has been
expanding rapidly in the past decade, the share of SBL to banking assets has become
significantly smaller now than it was over a decade ago (Figure 3.2). Following overall industry
trends, the ratio of SBL to assets has declined for all bank size groups, regardless of whether
they were involved in mergers and acquisitions (Figures 3.3 to 3.5). Interestingly, the decline in
the SBL ratio has been more severe at community banks than at larger banks. Large banks have
also been playing an increasing role in providing funding to small businesses in terms of SBL
volume and market share (Figure 3.1).
Regression Analysis — Community Bank Mergers and SBL: To further understand the
impact of community bank mergers on SBL, we perform a regression analysis in which we
control for the characteristics of the targets and the acquirers and the SBL trend for similar
banks (in the same size category and geographic location). The samples include all mergers that
15 For Figures 3.3 to 3.5, the data on SBL and assets are obtained from the year‐end quarterly Call Reports. The sample includes all mergers announced from 2000 to 2012 that involved community banks (targets being less than $1 billion in assets). The data are from the SNL database. 16 Figure 3.5 presents similar information to that in Figure 3.4 except that the amount of lending includes both the regular (nonfarm) SBL as well as farm SBL.
19
involved community banks during the period from 2000 to 2012. The summary statistics of the
sample are presented in Table 5.17
Dependent variables are measured in two different ways. First, we use the total
increased dollar amount (not adjusted for inflation) of SBL due to the mergers — estimated as
the combined firm’s total SBL after the merger minus the combined total SBL (the target and
the acquirer) prior to the merger. The results are presented in columns 1 and 2 of Table 6.
Second, we use the change in the ratio of SBL to assets for the combined (merged) banking firm
as compared with premerger. The premerger ratio is the combined SBL of the target and the
acquirer divided by the combined total assets of the target and the acquirer before the merger.
The results are presented in columns 3 and 4 of Table 6.
Independent variables include risk characteristics as reflected in the CAMELS ratings for
the targets and the acquirers prior to the merger in which the supervisory ratings have values
ranging from 1 (best) to 5 (worst). We also include dummy indicators for the size category (less
than $1 billion, between $1 billion and $10 billion, and larger than $10 billion) of the acquiring
banks, where the community bank acquirers, with assets of $1 billion or less, are included in the
analysis as the base case.
In addition, we control for the interaction between economic factors (such as the boom
period indicator) and asset size of the combined firm (by size category, with assets being less
than $1 billion, between $1 billion and $10 billion, and larger than $10 billion), where the boom
17 When CAMELS data are included in the analysis, the number of observations drops significantly. However, the sample distribution across bank size groups remains roughly the same for both the original (full) sample and the reduced sample (with no missing CAMELS). For acquirers, in the full sample, 27 percent of the banks are in the $1 billion to $10 billion range, 10 percent are in the more than $10 billion range, and the rest are in the less than $1 billion range. The numbers change only slightly to 25 percent in the $1 billion to $10 billion range and 6 percent in the larger than $10 billion range for the reduced sample, which is used for the regression analysis (with no missing CAMELS).
20
period is defined as the years from 2004 to 2007. This is intended to capture the varying
economic impact on SBL for the various size groups. Further, we control for whether the
merger is an assisted merger in which the target was failing. For this, we include a dummy
indicator for mergers that involved targets that were rated 4 or 5 (unsatisfactory) by their
supervisors.18
Controlling for the Overall SBL Market Trends: We control for the overall market trend
of SBL around the time of the merger announcement — to account for the SBL activities at
banks that did not merge and to account for the varying SBL activities both in tough economic
cycles (through time) and across banks. Specifically, this SBL market trend variable is included
to separate the change in SBL after mergers that may have been driven by factors other than
the merger, such as changes in SBL activities due to changes in the economic environment,
changes in demand and supply of SBL, regulatory changes, etc. The trend variable is calculated
for each observation, and it is defined as a percentage change in the overall SBL by all banks
(regardless of whether they merged) that are in the same size class as the combined merged
firm, in which the SBL change is measured over the same period based on the merged banking
firm’s merger date.19
From columns 1 and 2 in Table 6, controlling for all the risk characteristics of the targets
and the acquirers and economic factors as described earlier, the combined banking firms tend
to increase their overall SBL by a larger amount when the acquiring bank is very large (with
18 We also perform a separate analysis that excludes all 5‐rated banks and includes a control indicator for 4‐rated banks; the results are consistent with those presented in Table 6. 19 Until 2010, SBL was reported only once a year at the end of the second quarter. The trend control factor is measured as the one‐year change in the overall market (for the merged bank’s size group) around the merger date. For example, for a merger completed in November 2006, the trend variable would capture the change in SBL in the market from June 2005 to June 2006.
21
more than $10 billion in assets). This is reflected in the significantly positive coefficients of the
dummy indicator D_Largest_Acquirer_>$10Bill. In addition, the coefficient of the interactive
term D_Boom (2004‐2007)*D_Largest is also significantly positive, indicating that the increase
in the SBL amount (when the acquirers are in the largest size group) is even larger for those
mergers that took place during the boom period from 2004 to 2007. We find no significant
change in the SBL volume when the acquiring banks are either small community banks or
medium size (with assets less than $10 billion), after controlling for the risk characteristics,
economic conditions, and market trends.
When focusing on the change in ratio of SBL to assets, rather than the change in dollar
amount of SBL, the results in columns 3 and 4 of Table 6 show that the SBL ratio tends to
decline after the mergers when the acquiring banks are the largest or medium‐size banks
(larger than $10 billion in assets), as reflected in the significantly negative coefficients of
D_Large Acquirer_$1Bill to $10Bill and D_Largest Acquirer_>$10Bill. This is likely due to the
fact that these large acquiring institutions tend to grow more aggressively such that the overall
assets growth exceeds that of SBL.20 Nonetheless, the decline in the SBL ratio at large banks
overall is not as severe as that of the surviving community banks, as shown earlier in Figure 3.2.
We also control for failing targets, with the composite CAMELS rating being unsatisfactory
(rated 4 or 5) — the coefficients are consistently insignificant.
The SBL trend variable in Table 6, TREND_SBL Change_Size Group, is the average change
in the SBL ratio by all banks in the same size class around the merger announcement date,
20 Appendix 1 presents the plots of changes in SBL for the groups of merged banks compared with all other banks (merged and nonmerged banks combined) in the same size group. We find that changes in the SBL ratio due to mergers (that involved community bank targets) seem to be unrelated (or negatively correlated) to the overall SBL market trend (for the same size class).
22
regardless of whether they were involved in any merger transactions. The coefficients of this
SBL trend factor are significantly negative in column 2 (change in SBL volume) but insignificant
in column 4 (change in SBL ratio). Other control factors in Table 6 are the composite
supervisory ratings of the targets and the acquiring banks. They are generally not significantly
important in determining the change in SBL after the mergers — with only one exception (in
column 3) where it is weakly significantly positive at the 10 percent level, suggesting that the
SBL ratio may rise for mergers that involve poorly rated acquiring banks.21
The regression results confirm our previous findings that SBL activities, on average,
change significantly after the mergers. Specifically, SBL volume increases more when the
acquirers of community bank targets are large banks (larger than $10 billion). The change in
SBL is smaller for large acquirers than community bank acquirers, however, when considering
changes in SBL ratio (rather than volume). These results hold even after controlling for
important risk characteristics of the targets and acquirers, economic conditions, size‐related
factors, and market trends.
As mentioned earlier, SBL ratio for the industry overall actually declines more for
community banks than large banks, on average, over the recent years (Figure 3.2). In addition,
the roles of large banks in supporting small businesses have become increasingly important in
recent years with greater SBL market shares (Figure 3.1). The smaller SBL ratio to assets at
large banks suggests that the growth in loan demand for small business seems to be slower
than that of the overall banking assets in recent years.
21 We repeat the same analysis with the component CAMELS ratings as control factors, rather than the composite rating — the results are consistent with those reported in Table 6 (they are not presented here but are available upon request).
23
VI. MergerDealPremiumsandStockMarketReactions
Merger Deal Premiums: This section examines the merger deal premiums that acquirers
are willing to pay to acquire a community bank target. We perform a regression analysis, with
the dependent variable being the merger deal premiums, which are calculated as a ratio of
price per share paid by the acquirer divided by the market price per share of the target, based
on the target’s share price as of the day before the merger announcement date. The data on
mergers and share prices are obtained from the SNL database and Yahoo Finance.22
The analysis controls for the various risk characteristics of the targets and the acquirers,
including the ROE, efficiency ratio (the ratio of noninterest expense to the sum of net interest
income and other income), nonperforming loans (NPLs), capital adequacy, asset size of the
acquiring banks, market to book ratio, and an indicator for in‐state mergers. The acquirer’s size
indicators are calculated with inflation adjusted. All the risk characteristics are measured as of
the merger announcement date — calculated as the ratio of the acquirer’s characteristic to the
target’s characteristic. The market‐to‐book ratio is the ratio of the acquirer’s market‐to‐book
ratio to the target’s market‐to‐book ratio. The results are presented in Table 7.
The results indicate that merger premiums are smaller when the acquiring banks are
very large banks (with assets greater than $10 billion). The community bank targets were
willing to accept a smaller premium (or even a discount) to become a part of a large banking
organization — probably because large banks have greater ability to diversify, to obtain scale
and scope economies, and to better manage their operations. In addition, higher growth
22 Our analysis in this section includes a much smaller number of observations because most of the community banks that were involved in the mergers were not publicly traded; thus, their market share prices were not available.
24
acquirers (compared with the target), as measured by the ratio of market to book of the
acquirer and the target, are willing to pay more to acquire the community bank target.
Stock Market Reactions: Based on the subset data of community bank mergers that
involved publicly traded community bank targets, we examine how the stock market reacts to
the mergers, controlling for the various risk characteristics of the acquirers and the targets. We
perform a regression analysis with the dependent variable being cumulative abnormal returns
(CARs) around the merger announcement date (window ‐3 days to +3 days around the
announcement date).23 The abnormal returns are calculated based on an index of the 25
largest financial institutions, following the methodology used for the abnormal returns
calculation in Brook, Hendershott, and Lee (1998). Again, we control for the relative acquirer–
to‐target ratios for ROE, efficiency ratio, NPLs, and capital‐to‐assets ratio. The risk factors are
measured as of the merger’s announcement date. Relative asset size is the ratio of the target’s
assets to the acquirer’s assets. The acquirer’s size indicators are inflation adjusted. The merger
deal premium variable is the price per share that the acquirer paid to acquire the target divided
by the market price per share of the target (source: SNL database and Yahoo Finance). A
dummy indicator for low trading volume is also included to indicate that the bank’s stocks were
traded with an average of less than 1,000 shares daily for the period in which the market model
is fitted. The results are presented in Table 8.
After controlling for the risk characteristics of both the targets and the acquirers, the
results suggest that the stock market’s perception about these community bank mergers seems
to be determined by the merger deal premiums (i.e., the premiums that the acquirers are
23 We also perform the same analysis with different CARs windows, including (‐1, +1) and (‐1, +3). The results are not shown here, but they are consistent with those presented in Table 8.
25
willing to pay over the target’s market price per share). The larger the premiums that the
acquiring banks are willing to pay to acquire the community bank target, the larger the positive
abnormal returns around the merger announcement date. Given that the deal premiums that
acquirers are willing to pay are proxies for the synergies to be obtained from the mergers, the
results are consistent with an argument that the market reacts more positively to the mergers
that are expected to produce greater synergies.
VII. ConclusionsandPolicyImplications
There have been growing concerns about the potential of the decline in the number of
community banks and the increasing number of acquisitions of community banks by larger
banks — to disrupt local relationships and significantly reduce SBL.
In this paper, we examine the roles and characteristics of U.S. community banks in the
past decade, covering both the boom period and the subsequent downturn. We compare the
pre‐ and post‐merger performance and risk characteristics (including the confidential ratings
assigned by bank regulators), investigate whether the mergers have affected SBL, and observe
how the stock markets react to community bank mergers. We also explore whether large banks
have been able and willing to step in and substitute for community banks in providing funding
to small businesses.
We show that large banks have been getting larger and that the number of small banks
has been declining over the past two decades. However, from 2000 to 2012, as the number of
community banks has declined, we have found that the overall SBL market share for the largest
banks (more than $100 billion) has more than doubled; thereby indicating that large banks have
been stepping in to fill the gap.
26
Our regression analysis, controlling for risk characteristics of the targets and the
acquirers, economic factors, and market trends, finds that the amount of SBL by acquiring
banks tends to increase from the pre‐acquisition base when the acquirer is a large bank (with
assets of more than $10 billion), indicating that the large bank acquirers do grow SBL.
When examining SBL activities in terms of the average SBL‐to‐total‐asset ratio, the data
show that the SBL‐to‐assets ratio has declined (over the same period from 2001 to 2012) for all
bank size groups, including the community banks themselves. But the rate of decline among
large banks has been lower than that of community banks.
We find that community banks that were merged during the financial crisis period
performed poorly and were often rated unsatisfactory by their regulators on all risk aspects.
These community bank targets were undercapitalized, held poor quality and less liquid assets
on their balance sheet, were not profitable, and were not well managed. Our results overall
indicate that mergers of community bank targets with healthier banks have resulted in
combined banking firms that are healthier financially and more efficient in their operations.
Overall, mergers that involved community bank targets have so far enhanced the safety and
soundness of the banking system.
Among all community bank mergers that involved publicly traded targets, we find that
the merger premiums are smaller when the acquiring banks are large banks (with total assets
greater than $10 billion). This suggests that community bank targets may see an advantage in
becoming a part of large banking organizations and therefore may be willing to accept smaller
premiums (or even discounts).
27
Based on the above, we conclude that the trend of acquisitions of community banks by
large banks over the past decade has enhanced the overall safety and soundness of the banking
system, without adversely impacting SBL, as large banks have stepped in and grown their local
lending.24 This implies that a policy that discourages mergers between community banks and
large banks is unwarranted and could potentially result in a weaker financial system and have
an unintentional dampening effect on the supply of SBL lending.
24 Thirteen large banks pledged in September 2012 to boost lending to small businesses by $20 billion as of September 2014. These large banks include Bank of America Merrill Lynch, Citigroup, JPMorgan Chase & Co., PNC Bank N.A., TD Bank, U.S. Bank, Wells Fargo, KeyCorp, Regions Financial Corp., SunTrust Banks Inc., Citizens Financial Group Inc., Huntington Bancshares Inc., and M&T Bank Corp. As of September 2013, the banks had already boosted their SBL by $17 billion.
28
Table1NumberofBankingOrganizationsandShareofBankingAssets
byAssetSizeofBankingOrganizations Banking organizations include bank holding companies and independent commercial banks. Size thresholds are adjusted for inflation by using assets measured in 2006 prices.
Source: Call Reports (June data for each year)
Note:
It is shown above that both the total number of community banks (with total assets less than $1 billion) and their share of banking assets have declined significantly in the past decade. It should also be noted that most of the decline has been driven by very small community banks with assets less than $100 million. As expected, banks in all asset categories have become larger over time.
The share of U.S. banking assets has shifted significantly from small community banks to larger banks. Community banks held 18.4 percent of U.S. banking assets in 2001; that number fell to 9.7 percent in 2012. The share of U.S. banking assets (inflation adjusted) at the largest banks almost doubled during the same period.
Year
Number of Banking Organizations by Asset Size ($billions)
Share of Domestic Banking Assets (%) by Asset Size ($billions)
<$1 $1‐$10
$10‐$100 >$100 All <$1 $1‐$10
$10‐$100 >$100 All
2001 6850 275 53 6 7184 18.4 15.3 30.1 36.1 100.0
2002 6671 270 52 7 7000 18.0 14.3 25.7 42.0 100.0
2003 6521 277 60 7 6865 17.1 12.5 27.1 43.3 100.0
2004 6380 300 54 7 6741 16.0 12.8 24.6 46.7 100.0
2005 6240 312 54 7 6613 13.4 11.0 22.1 53.6 100.0
2006 6933 384 75 8 7400 12.6 11.3 27.5 48.6 100.0
2007 6795 394 68 13 7270 11.9 10.5 20.6 57.0 100.0
2008 6674 379 57 17 7127 11.3 9.7 16.8 62.1 100.0
2009 6440 406 63 18 6927 10.8 9.4 16.9 62.8 100.0
2010 6159 379 57 19 6614 10.6 8.9 14.7 65.8 100.0
2011 5897 375 61 17 6350 9.9 8.5 16.8 64.8 100.0
2012 5708 369 61 18 6156 9.7 8.5 15.9 65.9 100.0
Change 2001 to 2012 ‐1142 94 8 12 ‐1028 ‐8.8 ‐6.9 ‐14.2 29.8
29
Table2AcquisitionsofBankingOrganizations
byAssetSizeoftheTargets Banking organizations include bank holding companies and independent commercial banks. Size thresholds are adjusted for inflation by using assets measured in 2006 prices.
Year
Number of Acquisitions ($billions) by Target’s Asset Size
Amount of Assets Acquired ($billions) by Target’s Asset Size
<$1 $1‐$10
$10‐$100
>$100 All <$1 $1‐$10 $10‐$100
>$100 All
2000‐2004 810 67 18 4 899 140.3 172.0 526.1 937.4 1775.8
2005‐2006 412 28 7 0 447 73.6 70.1 220.0 0.0 363.8
2007‐2008 307 24 4 3 338 53.0 69.0 102.9 1017.8 1242.7
2009‐2010 342 28 6 0 376 69.3 77.0 114.3 0.0 260.6
2011‐2012 337 23 1 0 361 64.2 53.1 24.5 0.0 141.8
Total Number of Acquisitions
2208 91.2%
170 7.0%
36 1.5%
7 0.3%
2421 100%
400.4 10.6%
441.2 11.7%
987.8 26.2%
1955.251.9%
3764.7100%
Source: SNL database
Note: This table presents the merger trend over the study period. More than 90 percent of the mergers that took place from 2000 to 2012 involved community bank targets. This number, however, accounts for only slightly more than 10 percent in terms of all targets’ banking assets.
30
Table3AcquisitionsofCommunityBanks
byAssetSizeofAcquirersBanking organizations include bank holding companies and independent commercial banks. Size thresholds are adjusted for inflation by using assets measured in 2006 prices.
Year
Number of Community Bank Acquisitions ($billion)
by Buyer’s Asset Size
Amount of Community Bank Assets Acquired ($billion) by Buyer’s Asset Size
<$1 $1‐$10
$10‐$100 >$100 All <$1 $1‐$10
$10‐$100 >$100 All
1990‐1994
946 61%
388
196
11
1541 100%
69 36%
71
45
4.1
189 100%
1995‐1999
692 49%
458
218
34
1402 100%
62 28%
92
58
8.3
221 100%
2000‐2004
467 58%
257
80
6
810 100%
44 32%
62
31
2.5
140 100%
2005‐2006
243 59%
137
24
8
412 100%
28 38%
32
10
2.6
73 100%
2007‐2008
217 71%
74
14
2
307 100%
24 46%
22
6
0.8
53 100%
2009‐2010
312 91%
29
0
1
342 100%
61 88%
8
0
0.4
69 100%
2011‐2012
261 77%
69
6
1
337 100%
44 69%
18
2
0.4
64 100%
Total
3138 61%
1412 27%
538 10%
63 1%
5151 100%
333 41%
304 37%
153 19%
19 2%
811 100%
Source: SNL database
Note:
This table shows that community banks have been acquired mostly by other community banks throughout the study period, especially during the period after the recent financial crisis had begun.
In 2007, about 50 to 60 percent of community bank mergers involved community bank acquirers. After 2007, the ratio increased to more than 70 percent and peaked at more than 90 percent from 2009 to 2010.
The asset value of acquisitions by community bank acquirers also rose significantly during the postfinancial crisis period from 2009 to 2010.
31
Table4In‐Statevs.Out‐of‐StateMergersofCommunityBanksThatWereAcquiredbyOtherCommunityBanks
The sample includes all bank mergers in which both the targets and the acquirers are U.S. commercial banks or bank holding companies with total assets less than $1 billion (in 2006 prices).
Year
Number of Community Bank Acquisitions
Amount of Community Bank Assets Acquired ($billion)
In‐State Out‐of‐State In‐State Out‐of‐State
1990‐1994 937 87%
137 13%
115 61%
75 39%
1995‐1999 718 89%
86 11%
125 56%
96 44%
2000‐2004 445 82%
97 18%
85 61%
55 39%
2005‐2006 212 79%
57 21%
44 60%
29 40%
2007‐2008 204 80%
50 20%
35 66%
18 34%
2009‐2010 257 66%
132 32%
45 65%
24 35%
2011‐2012 237 77%
70 23%
40 63%
24 37%
Total
3010 82.7%
629 17.3%
490 60.4%
321 39.6%
Source: SNL database
Note:
This table shows that community bank mergers (mergers between the community bank target and the community bank acquirer) have mostly been within the same state (in‐state mergers).
Out‐of‐state mergers account for less than 20 percent of all community bank mergers in terms of numbers and less than 40 percent when measured in terms of banking assets.
32
Table5SummaryStatisticsoftheFullSample
Variable N Mean Minimum Maximum Std Dev N Miss
Relative Size (Target/Acquirer)
D_Acquirer Size $1‐$10 Billion
D_Acquirer Larger Than $10 Billion
ROE Ratio (Acquirer/Target)
Efficiency Ratio (Acquirer/Target)
NPA Ratio (Acquirer/Target)
Capital Asset Ratio (Acquirer/Target)
Acquirer_C Rating
Acquirer_A Rating
Acquirer_M Rating
Acquirer_E Rating
Acquirer_L Rating
Acquirer S Rating
Acquirer_Composite CAMELS
Target_C Rating
Target_A Rating
Target_M Rating
Target_E Rating
Target_L Rating
Target S Rating
Target_Composite CAMELS
D_In‐State Mergers
DealPremium1DayBefore
DealPremium2DayBefore
DealPremium3DayBefore
CAR_Window ‐1, +1
CAR_Window ‐3, +3
CAR_Window ‐1, +3
1658
2230
2230
1606
1563
1277
1659
1588
1610
1588
1592
1590
1582
1597
1606
1615
1610
1610
1611
1591
1608
2230
293
303
309
576
576
576
0.284
0.253
0.063
1.170
0.869
3.565
‐0.507
1.594
1.696
1.687
1.773
1.610
1.645
1.670
2.492
2.531
2.681
2.916
2.278
2.389
2.666
0.722
35.038
38.337
40.715
‐0.004
‐0.005
‐0.005
0.00007
0
0
‐201.606
‐48.159
0
‐2693.87
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0
‐49.600
‐31.370
‐31.370
‐0.5165
‐0.2841
‐0.2537
13.940
1.00
1.00
193.662
3.3557
200.031
12.048
5.00
5.00
5.00
5.00
4.00
4.00
5.00
5.00
5.00
5.00
5.00
5.00
5.00
5.00
1.00
96.880
119.740
137.700
0.3477
0.3296
0.3546
0.6629
0.4352
0.2442
10.0735
1.2742
12.8812
66.1690
0.5561
0.7025
0.5685
0.7509
0.5461
0.5498
0.5442
1.4672
1.5128
1.3520
1.4022
1.3139
1.1455
1.4021
0.4476
25.2010
27.5024
30.6425
0.0519
0.0598
0.0538
572
0
0
624
667
953
571
642
620
642
638
640
648
633
624
615
620
620
619
639
622
0
1937
1927
1921
1654
1654
1654
33
Table6SmallBusinessLendingRegressions
The samples include all mergers that involved community banks during the period from 2000 to 2012. Supervisory ratings have a value of 1 (best) to 5 (worst). Community bank acquirers (with assets up to $1 billion) are included in the analysis as the base case. The increase in SBL (includes both farm and nonfarm SBL) due to mergers is calculated as the difference (not adjusted for inflation) between SBL by the combined firm after the merger and the combined SBL of the target and the acquirer prior to the merger. Standard errors are reported in parentheses under the coefficients. The significance levels are calculated with heteroscedasticity‐consistent standard errors, where ***, **, and * represent significance at the 1 percent, 5 percent, and 10 percent levels, respectively.
Independent Variables
$ Increased SBL After M&A SBL/Assets Ratio After M&A
(1) (2) (3) (4)
Intercept D_Large Acquirer_$1Bill to $10Bill D_Largest Acquirer_> $10Bill D_Boom (2004‐2007)*D_Large D_Boom (2004‐2007)*D_Largest D_Failing Target (4‐5 Rated) TREND_SBL Change_Size Group Acquirer_Composite CAMELS Target_Composite CAMELS
6450.81(19776.78) ‐4462.10 (12905.91)
235,460.54*** (25298.30) 15270.68 (17356.39) 89004.29** (38023.39) 4340.26
(23605.85)
4684.41 (8379.62) ‐5845.41 (7475.89)
24157.17(21032.40) ‐1303.96 (10655.19)
274848.47*** (19858.60)
‐3191.54 (23760.00)
‐123905.17** (52126.92) 3042.56 (8390.49) ‐6913.00 (7485.27)
0.1328*** (0.0310)
‐0.1191*** (0.0202)
‐0.1252*** (0.0399) 0.0152 (0.0277) ‐0.0010 (0.0614) ‐0.0208 (0.0375)
0.0227* (0.0134) ‐0.0140 (0.0117)
0.1464***(0.0329)
‐0.1151*** (0.0167)
‐0.1234*** (0.0317)
‐0.0255 (0.0377) ‐0.0951 (0.0829) 0.0211 (0.0134) ‐0.0147 (0.0117)
R‐Square Adjusted R‐Square Observation Number (N)
16.59% 16.05% 1087
16.54% 16.08% 1087
5.89% 5.37% 960
5.99% 5.40% 960
34
Table7CommunityBankMerger—DealPremiums
The merger deal premiums are calculated based on the target’s share price as of one day before the merger announcement date. The acquirer’s size indicators are inflation adjusted. The merger deal premium is the price per share that the acquirer paid to acquire the target divided by market price per share of the target (sources: SNL database and Yahoo Finance). All the risk characteristics (ROE, efficiency ratio, NPLs, capital‐to‐assets ratio, market‐to‐book ratio) are measured as of the merger’s announcement date — acquirer‐to‐target ratio. The market‐to‐book ratio is the ratio of the acquirer’s market‐to‐book ratio to the target’s market‐to‐book ratio. Standard errors are reported in parentheses under the coefficients. The significance levels are calculated with heteroscedasticity‐consistent standard errors, where ***, **, and * represent significance at the 1 percent, 5 percent, and 10 percent levels, respectively.
Model (1) (4) (7)
Intercept D_Mergers Announced in 2003‐2007 D_Mergers Announced in 2008‐2010 D_Mergers Announced in 2011 or Later D_$1 Billion < Acquirer Size > $10Billion D_Acquirer Asset Size > $10 Billion ROE Ratio_Acquirer to Target Efficiency Ratio_Acquirer to Target NPL Ratio_Acquirer to Target Capital Ratio_Acquirer to Target Market‐to‐Book_Acquirer to Target D_In‐State Mergers
46.4153*** (12.0062)
‐‐ ‐‐ ‐‐
‐0.4798 (4.7004) ‐10.7393* (5.7128) ‐0.1446 (0.1891) ‐12.0745 (10.6378) 0.1868 (0.2277) 1.8847 (2.9373)
‐‐
‐1.5262 (4.4637)
16.8278 (14.9138)
‐‐ ‐‐ ‐‐
1.9512 (4.8895)
‐12.0855** (5.6041) ‐0.1432 (0.5100) ‐8.7366 (11.2318) 0.4726*** (0.1683) 5.8738 (3.7927)
15.2883*** (3.6965) ‐1.8270 (4.7382)
19.7697 (16.1707) ‐2.8784 (4.2457) 3.7930 (8.6852) 3.8699 (6.4883) 2.0128 (4.9228) ‐11.5112* (5.8775) ‐0.1109 (0.4982) ‐8.7455 (11.1935) 0.5053*** (0.1593) 4.9612 (3.8398)
13.7855*** (4.1138) ‐1.8626 (4.7850)
R‐Square Adjusted R‐Square RMSE Observation Number
0.0341 ‐0.0047 25.8544 182
0.148 0.101
24.4372 154
0.1569 0.0916 24.5649 154
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Table8StockMarketReactions
CumulativeAbnormalReturns(CARs)Regressions The cumulative abnormal returns (CARs) are calculated for the window (‐3, +3) around the merger announcement date, based on an index of the 25 largest financial institutions. Relative asset size is the ratio of the target’s assets to the acquirer’s assets. The acquirer’s size indicators are inflation adjusted. The merger deal premium is the price per share that the acquirer paid to acquire the target divided by the market price per share of the target (sources: SNL database and Yahoo Finance). All the risk characteristics (ROE, efficiency ratio, NPLs, capital‐to‐assets ratio) are measured as of the merger’s announcement date — acquirer‐to‐target ratio. The dummy indicator for low trading volume indicates that the bank’s stocks were traded with an average of less than 1,000 shares daily for the period in which the market model is fit. Standard errors are reported in parentheses under the coefficients. The significance levels are calculated with heteroscedasticity‐consistent standard errors, where ***, **, and * represent significance at the 1 percent, 5 percent, and 10 percent levels, respectively.
(1) (2) (3)
Intercept Relative Asset Size_Target to Acquirer D_Acquirer Asset Size > $1Billion D_Acquirer Asset Size > $10Billion D_In‐State Mergers Merger Deal Premium ROE Ratio_Acquirer to Target Efficiency Ratio_Acquirer to Target NPL Ratio_Acquirer to Target Capital Ratio_Acquirer to Target D_Low Trading Volume D_Mergers Announced in 2003‐2007 D_Mergers Announced in 2008‐2010 D_Mergers Announced in 2011 or Later
‐0.014** (0.0072) 0.035** (0.0150) 0.012* (0.0059) 0.012
(0.0081) 0.001
(0.0047) ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
‐0.026 (0.0164) 0.015
(0.0234) 0.0105 (0.0120) 0.0109 (0.0162) 0.0002 (0.0083) 0.0006*** (0.0002)
‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐ ‐‐
‐0.057 (0.0442) ‐0.0093 (0.0550) 0.003
(0.0239) ‐0.004 (0.0309) ‐0.006 (0.0147) 0.0007** (0.0003) 0.0003 (0.0021) 0.027
(0.0323) ‐0.001 (0.0007) 0.019
(0.0165) 0.00049 (0.027) 0.0041 (0.016) 0.001
(0.0203) 0.004
(0.0206)
R‐Square Adjusted R‐Square RMSE Observation Number
1.50% 0.56% 0.0436 132
12.59% 9.12% 0.0417 132
0.17.67% 12.37% 0.0547 84
36
References
Agarwal, Sumit, Divid Lucca, Amit Seru, and Francesco Trebbi (2014). “Inconsistent Regulators: Evidence from Banking,” Quarterly Journal of Economics (forthcoming). Avery, Robert, and Katherine Samolyk (2004). “Bank Consolidation and Small Business Lending: The Role of Community Banks” Journal of Financial Services Research, 25 (2), 291‐326. Beccalli, Elena, and Pascal Frantz (2013). “The Determinants of Mergers and Acquisitions in Banking,” Journal of Financial Services Research 43 (3), 265‐291. Berger, Allen (2014). “Small Business Lending by Banks: Lending Technologies and the Effects of Banking Industry Consolidation and Technological Change,” Oxford Handbook of Banking, Chapter 12, forthcoming. Berger, Allen, Geraldo Cerqueiro, and Maria Fabiana Penas (2014). “Market Size Structure and Small Business Lending: Are Crisis Times Different from Normal Times?” Review of Finance, 1‐31. Berger, Allen, William Goulding, and Tara Rice (2014) “Do Small Businesses Still Prefer Community Banks?” Journal of Banking and Finance 44, 264‐278. Berger, Allen, Adrian Cowan, and Scott Frame (2011). “The Surprising Use of Credit Scoring in Small Business Lending by Community Banks and the Attendant Effects on Credit Availability, Risk, and Profitability,” Journal of Financial Services Research 39, 1‐17. Berger, Allen, and Gregory Udell (2006). “A More Complete Conceptual Framework for SME Finance,” Journal of Banking and Finance 30, 2945‐2966. Berger, Allen, Joseph Scalise, Anthony Saunders, and Gregory Udell (1998). “The Effects of Bank Mergers and Acquisitions on Small Business Lending” Journal of Financial Economics, 50(2), 187‐229. Berger, Allen, Seth Bonime, Lawrence Goldberg, and Lawrence White (2004). “The Dynamics of Market Entry: The Effects of Mergers and Acquisitions on Entry in the Banking Industry,” Journal of Business 77 (October), 797‐834. Berger, Allen, Scott Frame, and Nathan Miller (2005). “Credit Scoring and the Availability, Price, and Risk of Small Business Credit,” Journal of Money, Credit, and Banking 37, 191‐222. Brook, Yaron, Robert Hendershott, and Darrell Lee (1998). “The Gains from Takeover Deregulation: Evidence from the End of Interstate Banking Restrictions,” Journal of Finance 53, (6), 2185‐2204.
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Conference of State Bank Supervisors (2014), “2013 Annual Report of the Conference of State Bank Supervisors” May. Cooper, Elizabeth, and Todd Vermilyea (2012). “The Impact of Management Quality on Merger Outcomes,” Federal Reserve Board, unpublished manuscript. DeYoung, Robert, Lawrence Goldberg, and Lawrence White (1999). “Youth, Adolescence, and Maturity of Banks: Credit Availability to Small Business in an Era of Banking Consolidation,” Journal of Banking and Finance 23, 463‐492. Elyasiani, Elyas, and Lawrence Goldberg (2004). “Relationship Lending: A Survey of the Literature” Journal of Economics and Business 56, 315‐330. Goldberg, Lawrence, and Lawrence White (1998). “De Novo Banks and Lending to Small Business: An Empirical Analysis,” Journal of Banking and Finance 22, 851‐867. Jagtiani, Julapa (2008). “Understanding the Effects of the Merger Boom on Community Banks,” Federal Reserve Bank of Kansas City: Economic Review, Second Quarter, 29‐48. Kowalik, Michal (2014). “Can Small Banks Survive Competition from Large Banks?” Federal Reserve Bank of Boston, Working Paper.
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Appendix 1
The plots in this appendix illustrate the one‐year and two‐year changes in small business lending (SBL) during the periods one‐year and two‐years following the merger dates. The goal is to compare the changes in SBL at merged banks (our sample banks) with the overall market (all banks in the U.S.) — to explore whether the SBL changes following the mergers were driven by the mergers or simply reflect the changes in market conditions. A separate analysis was performed for each size groups, resulting in three plots below. The banks are grouped by the asset size of the combined entity postmerger (for the sampled merged banks) and by asset size of each individual bank in the market (for nonmerged banks). Data are from the SNL financial database and the Federal Reserve Call Report (June) data. The results from these figures indicate that SBL at sampled merged banks tends to move largely independently of the overall SBL in the same time period. What we observe from these plots is consistent with the regression results in Table 6, which indicate that SBL at merged banks in our sample tended to, on average, move in the opposite direction of the market. The results could also imply that banks that acquire community banks, as a size class, tend to be different from banks that generally make up the market (nonmerged banks) in terms of their SBL.
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